Measurement and Early Warning of Systemic Financial Risk in China: Markov Switching Models

Yingdong Wang () and Wenzhi Xi ()
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Yingdong Wang: Wuhan University of Science and Technology, School of Law and Economics
Wenzhi Xi: Zhongnan University of Economics and Law, School of Statistics and Mathematics

Computational Economics, 2025, vol. 66, issue 6, No 23, 5083-5111

Abstract: Abstract With the ongoing financialization and informatization of the global economy, the sources of financial risk have become more diverse and concealed, leading to an increase in systemic financial risk. Using monthly data from China from January 2005 to March 2024, we measure systemic financial risk through a financial stress index, considering seven dimensions: the banking sector, stock market, bond market, money market, real estate market, macroeconomic environment, and international financial risk contagion. We also introduce an innovative approach by combining the Markov regime-switching model with the Markov switching multifractal model to create a more comprehensive and effective early warning system of systemic financial risk. Our study reveals strong interconnections among China’s financial submarkets, with systemic financial risk originating primarily from the stock market, bond market, and macroeconomic environment. Furthermore, systemic financial risk in China tends to be more stable in low-risk states, whereas high-risk states are usually short-lived.

Keywords: Systemic financial risk; Financial stress index; Markov regime-switching model; Markov switching multifractal model; Early warning system (search for similar items in EconPapers)
JEL-codes: G01 G15 G17 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10614-025-10873-9

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